Hydration of Atmospheric Molecular Clusters III: Procedure for Efficient Free Energy Surface Exploration of Large Hydrated Clusters

Computational Tools for Handling Molecular Clusters: Configurational Sampling, Storage, Analysis, and Machine Learning

Computational modeling of atmospheric molecular clusters requires a comprehensive understanding of their complex configurational spaces, interaction patterns, stabilities against fragmentation, and even dynamic behaviors. To address these needs, we introduce the Jammy Key framework, a collection of automated scripts that facilitate and streamline molecular cluster modeling workflows. Jammy Key handles file manipulations between varieties of integrated third-party programs. The framework is divided into three main functionalities: (1) Jammy Key for configurational sampling (JKCS) to perform systematic configurational sampling of molecular clusters, (2) Jammy Key for quantum chemistry (JKQC) to analyze commonly used quantum chemistry output files and facilitate database construction, handling, and analysis, and (3) Jammy Key for machine learning (JKML) to manage machine learning methods in optimizing molecular cluster modeling. This automation and machine learning utilization significantly reduces manual labor, greatly speeds up the search for molecular cluster configurations, and thus increases the number of systems that can be studied. Following the example of the Atmospheric Cluster Database (ACDB) of Elm (ACS Omega, 4, 10965-10984, 2019), the molecular clusters modeled in our group using the Jammy Key framework have been stored in an improved online GitHub repository named ACDB 2.0. In this work, we present the Jammy Key package alongside its assorted applications, which underline its versatility. Using several illustrative examples, we discuss how to choose appropriate combinations of methodologies for treating particular cluster types, including reactive, multicomponent, charged, or radical clusters, as well as clusters containing flexible or multiconformer monomers or heavy atoms. Finally, we present a detailed example of using the tools for atmospheric acid-base clusters.

Roles of Amides on the Formation of Atmospheric HONO and the Nucleation of Nitric Acid Hydrates

Nitrous acid (HONO) is hazardous to the human respiratory system, and the hydrolysis of NO₂ is the source of HONO. Hence, the investigation on the removal and transformation of HONO is urgently established. The effects of amide on the mechanism and kinetics of the formation of HONO with acetamide, formamide, methylformamide, urea, and its clusters of the catalyst were studied theoretically. The results show that amide and its small clusters reduce the energy barrier, the substituent improves the catalytic efficiency, and the catalytic effect order is dimer > monohydrate > monomer. Meanwhile, the clusters composed of nitric acid (HNO₃), amides, and 1-6 water molecules were investigated in the amide-assisted nitrogen dioxide (NO₂) hydrolysis reaction after HONO decomposes by combining the system sampling technique and density functional theory. The study on thermodynamics, intermolecular forces, optics properties of the clusters, as well as the influence of humidity, temperature, atmospheric pressure, and altitude shows that amide molecules promote the clustering and enhance the optical properties. The substituent facilitates the clustering of amide and nitric acid hydrate and lowers the humidity sensitivity of the clusters. The findings will help to control the atmospheric aerosol particle and then reduce the harm of poisonous organic chemicals on human health.

The driving effects of common atmospheric molecules for formation of prenucleation clusters: the case of sulfuric acid, formic acid, nitric acid, ammonia, and dimethyl amine

How secondary aerosols form is critical as aerosols' impact on Earth's climate is one of the main sources of uncertainty for understanding global warming. The beginning stages for formation of prenucleation complexes, that lead to larger aerosols, are difficult to decipher experimentally. We present a computational chemistry study of the interactions between three different acid molecules and two different bases. By combining a comprehensive search routine covering many thousands of configurations at the semiempirical level with high level quantum chemical calculations of approximately 1000 clusters for every possible combination of clusters containing a sulfuric acid molecule, a formic acid molecule, a nitric acid molecule, an ammonia molecule, a dimethylamine molecule, and 0-5 water molecules, we have completed an exhaustive search of the DLPNO-CCSD(T)/CBS//ωB97X-D/6-31++G** Gibbs free energy surface for this system. We find that the detailed geometries of each minimum free energy cluster are often more important than traditional acid or base strength. Addition of a water molecule to a dry cluster can enhance stabilization, and we find that the (SA)(NA)(A)(DMA)(W) cluster has special stability. Equilibrium calculations of SA, FA, NA, A, DMA, and water using our quantum chemical ΔG° values for cluster formation and realistic estimates of the concentrations of these monomers in the atmosphere reveals that nitric acid can drive early stages of particle formation just as efficiently as sulfuric acid. Our results lead us to believe that particle formation in the atmosphere results from the combination of many different molecules that are able to form highly stable complexes with acid molecules such as SA, NA, and FA.

Hydrogen-Bond Topology Is More Important Than Acid/Base Strength in Atmospheric Prenucleation Clusters

We explored the hypothesis that on the nanoscale level, acids and bases might exhibit different behavior than in bulk solution. Our study system consisted of sulfuric acid, formic acid, ammonia, and water. We calculated highly accurate Domain-based Local pair-Natural Orbital- Coupled-Cluster/Complete Basis Set (DLPNO-CCSD(T)/CBS) energies on DFT geometries and used the resulting Gibbs free energies for cluster formation to compute the overall equilibrium constants for every possible cluster. The equilibrium constants combined with the initial monomer concentrations were used to predict the formation of clusters at the top and the bottom of the troposphere. Our results show that formic acid is as effective as ammonia at forming clusters with sulfuric acid and water. The structure of formic acid is uniquely suited to form hydrogen bonds with sulfuric acid. Additionally, it can partner with water to form bridges from one side of sulfuric acid to the other, hence demonstrating that hydrogen bonding topology is more important than acid/base strength in these atmospheric prenucleation clusters.

Synergistic effect of glutaric acid and ammonia/amine/amide on their hydrates in the clustering: A theoretical study

The formation of molecular clusters makes influence on the atmosphere. The clusters of glutaric acid (GA) and common ammonia (A), amine (methylamine MA, dimethylamine DMA) and representative amide (urea U) along with water molecule were systematically studied theoretically. GA-A-nW (n = 1, 2), GA-MA-nW (n = 1, 2), GA-DMA-1W and GA-U-nW (n = 1-6) are predicted to be feasible thermodynamically with the hydrogen bonds as interaction force. GA and urea promote the clustering synergistically, and ammonia, methylamine, dimethylamine promote the clustering of small GA hydrates (n = 1-2), while inhibit that of large GA hydrates (n = 3-6). The results of humidity show that un-hydrate or mono-hydrate is the main form of GA-mbase-nW (m = 0, 1; n = 1-6) under relative humidity of 20%, 50% and 80%. The global minima remain dominant over the temperature range of 220-320 K. GA contributes more to the Rayleigh scattering properties than sulfuric acid. More importantly, the local minima can undergo isomerization to form the global minima crossing a free energy barrier ranging from 6.66 to 11.78 kcal mol^-1. This study indicates that GA and base molecules play a synergistic role to promote the formation of clusters. We hope it can provide more insights on interesting clustering in theory.

Molecular properties affecting the hydration of acid-base clusters

In the atmosphere, water in all phases is ubiquitous and plays important roles in catalyzing atmospheric chemical reactions, participating in cluster formation and affecting the composition of aerosol particles. Direct measurements of water-containing clusters are limited because water is likely to evaporate before detection, and therefore, theoretical tools are needed to study hydration in the atmosphere. We have studied thermodynamics and population dynamics of the hydration of different atmospherically relevant base monomers as well as sulfuric acid-base pairs. The hydration ability of a base seems to follow in the order of gas-phase base strength whereas hydration ability of acid-base pairs, and thus clusters, is related to the number of hydrogen binding sites. Proton transfer reactions at water-air interfaces are important in many environmental and biological systems, but a deeper understanding of their mechanisms remain elusive. By studying thermodynamics of proton transfer reactions in clusters containing up to 20 water molecules and a base molecule, we found that that the ability of a base to accept a proton in a water cluster is related to the aqueous-phase basicity. We also studied the second deprotonation reaction of a sulfuric acid in hydrated acid-base clusters and found that sulfate formation is most favorable in the presence of dimethylamine. Molecular properties related to the proton transfer ability in water clusters are discussed.

Toward a Holistic Understanding of the Formation and Growth of Atmospheric Molecular Clusters: A Quantum Machine Learning Perspective

The formation of atmospheric molecular clusters is an important stage in forming new particles in the atmosphere. Despite being a highly focused research area, the exact chemical species involved in the initial steps in new particle formation remain elusive. In this Perspective the main challenges and recent progression in the field are outlined with a special emphasis on the chemical complexity of the puzzle and prospect of modeling larger clusters. In general, there is a high demand for accurate and more complete quantum chemical data sets that can be applied in cluster distribution dynamics models and coupled to atmospheric chemical transport models. A view on how the community could reach this goal by applying data-driven machine learning approaches for more efficient exploration of cluster configurations is presented. A path toward larger clusters and direct molecular dynamics simulations of cluster formation and growth using machine learning models is discussed.

Hydration motifs of ammonium bisulfate clusters show complex temperature dependence

The role of water in the formation of particles from atmospheric trace gases is not well understood, in large part due to difficulties in detecting its presence under atmospheric conditions and the variety of possible structures that must be screened computationally. Here, we use infrared spectroscopy and variable-temperature ion trap mass spectrometry to investigate the structural motifs adopted by water bound to ammonium bisulfate clusters and their temperature dependence. For clusters featuring only acid-base linkages, water adopts a bridging arrangement spanning an adjacent ammonium and bisulfate. For larger clusters, water can also insert into a bisulfate-bisulfate hydrogen bond, yielding hydration isomers with very similar binding energies. The population of these isomers shows a complex temperature evolution, as an apparent third isomer appears with a temperature dependence that is difficult to explain using simple thermodynamic arguments. These observations suggest that the thermodynamics of water binding to atmospheric clusters such as these may not be straightforward.